Literature DB >> 32977303

Objective scoring of streetscape walkability related to leisure walking: Statistical modeling approach with semantic segmentation of Google Street View images.

Shohei Nagata1, Tomoki Nakaya2, Tomoya Hanibuchi3, Shiho Amagasa4, Hiroyuki Kikuchi5, Shigeru Inoue6.   

Abstract

Although the pedestrian-friendly qualities of streetscapes promote walking, quantitative understanding of streetscape functionality remains insufficient. This study proposed a novel automated method to assess streetscape walkability (SW) using semantic segmentation and statistical modeling on Google Street View images. Using compositions of segmented streetscape elements, such as buildings and street trees, a regression-style model was built to predict SW, scored using a human-based auditing method. Older female active leisure walkers living in Bunkyo Ward, Tokyo, are associated with SW scores estimated by the model (OR = 3.783; 95% CI = 1.459 to 10.409), but male walkers are not.
Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.

Entities:  

Keywords:  Deep learning; Google street view; Neighborhood walkability; Semantic segmentation; Walking behavior

Year:  2020        PMID: 32977303     DOI: 10.1016/j.healthplace.2020.102428

Source DB:  PubMed          Journal:  Health Place        ISSN: 1353-8292            Impact factor:   4.078


  5 in total

1.  Using machine learning to examine street green space types at a high spatial resolution: Application in Los Angeles County on socioeconomic disparities in exposure.

Authors:  Yi Sun; Xingzhi Wang; Jiayin Zhu; Liangjian Chen; Yuhang Jia; Jean M Lawrence; Luo-Hua Jiang; Xiaohui Xie; Jun Wu
Journal:  Sci Total Environ       Date:  2021-05-08       Impact factor: 10.753

2.  Assessing Inequity in Green Space Exposure toward a "15-Minute City" in Zhengzhou, China: Using Deep Learning and Urban Big Data.

Authors:  Jingjing Luo; Shiyan Zhai; Genxin Song; Xinxin He; Hongquan Song; Jing Chen; Huan Liu; Yuke Feng
Journal:  Int J Environ Res Public Health       Date:  2022-05-10       Impact factor: 4.614

3.  Measuring Perceived Psychological Stress in Urban Built Environments Using Google Street View and Deep Learning.

Authors:  Xin Han; Lei Wang; Seong Hyeok Seo; Jie He; Taeyeol Jung
Journal:  Front Public Health       Date:  2022-05-11

4.  Preference for Street Environment Based on Route Choice Behavior While Walking.

Authors:  Lan Jin; Wei Lu; Peijin Sun
Journal:  Front Public Health       Date:  2022-08-05

5.  Street images classification according to COVID-19 risk in Lima, Peru: a convolutional neural networks feasibility analysis.

Authors:  Rodrigo M Carrillo-Larco; Manuel Castillo-Cara; Jose Francisco Hernández Santa Cruz
Journal:  BMJ Open       Date:  2022-09-19       Impact factor: 3.006

  5 in total

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